def test_correct_marginal_fails_vars(self):
"""
Test that the get_marginal function fails when there is no factor containing the variables to keep.
"""
g_1 = make_random_gaussian(["a", "b"])
g_2 = make_random_gaussian(["b", "c"])
cga = ClusterGraph([g_1, g_2])
cga.process_graph()
with self.assertRaises(ValueError):
cga.get_marginal(["a", "c"])
def test_correct_marginal_special_evidence(self):
"""
Test that the get_marginal function returns the correct marginal after a graph with special evidence has been
processed.
"""
factors = [self.p_a, self.p_b_g_a, self.p_c_g_a]
cga = ClusterGraph(factors, special_evidence={"a": 3.0})
cga.process_graph(max_iter=1)
vrs = ["b"]
cov = [[1.9]]
mean = [[2.7002]]
log_weight = -2.5202640960492313
expected_posterior_marginal = Gaussian(var_names=vrs,
cov=cov,
mean=mean,
log_weight=log_weight)
actual_posterior_marginal = cga.get_marginal(vrs=["b"])
actual_posterior_marginal._update_covform()
self.assertTrue(
expected_posterior_marginal.equals(actual_posterior_marginal))